Animal Fat Intake Is Associated with Albuminuria in Patients with Non-Alcoholic Fatty Liver Disease and Metabolic Syndrome.
Manuela AbbateCatalina M MascaróSofía MontemayorMaría Barbería-LatasaMiguel CasaresCristina GómezLucia UgarrizaSilvia TejadaJosé Alfredo MartínezMaría de Los Ángeles ZuletAntoni Sureda GomilaJosé Alfredo Martínez HernándezJosep Antonio TurPublished in: Nutrients (2021)
Non-alcoholic fatty liver disease (NAFLD) and metabolic syndrome (MetS) are associated with chronic kidney disease (CKD). Diet could play a predisposing role in the development of increased albuminuria in patients with NAFLD and MetS; however, published evidence is still limited. The aim of this cross-sectional analysis was to assess whether dietary fats are associated with changes in urinary albumin-to-creatinine ratio (UACR) in 146 patients aged 40-60-years with NAFLD and MetS. Dietary data were collected by food frequency questionnaire; UACR was measured in a single first morning void. Sources and types of dietary fats used in the analysis were total fat, fats from animal and vegetable sources, saturated, monounsaturated, polyunsaturated, and trans fats. One-way analysis of variance was performed to assess differences in dietary fats intakes across stages of UACR. The association between dietary fats and UACR was assessed by Pearson's correlation coefficient and multivariable linear regression. Patients with increased UACR showed a worse cardiometabolic profile and higher intakes of animal fat, as compared to patients with normal levels of albuminuria. Animal fat intake was associated with mean UACR, independent of potential covariates.
Keyphrases
- chronic kidney disease
- end stage renal disease
- metabolic syndrome
- adipose tissue
- fatty acid
- cross sectional
- peritoneal dialysis
- uric acid
- systematic review
- insulin resistance
- physical activity
- drinking water
- weight loss
- computed tomography
- type diabetes
- patient reported
- weight gain
- magnetic resonance imaging
- climate change
- risk assessment
- cardiovascular risk factors
- human health
- diffusion weighted imaging
- patient reported outcomes
- big data
- meta analyses